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Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

DOI: 10.1186/1750-0680-8-1

Keywords: Forest, Carbon density, Imputation, United States, Forest inventory, Raster maps

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Forest ecosystems represent the largest terrestrial carbon (C) sink on earth [1,2], such that the United Nations Framework Convention on Climate Change [3] has recognized their management as an effective strategy for offsetting greenhouse gas (GHG) emissions [4,5]. As part of the Convention, the U.S. has been submitting national reports, the National Greenhouse Gas Inventory (NGHGI), detailing emissions and removals of GHGs [3] on an annual basis for many years [6]. In addition to international reporting requirements, GHG budgets are being developed at sub-national scales including states (e.g., California) and ownerships (e.g, National Forest System climate change scorecard). Forest C stocks in the U.S. are estimated using data from the national forest inventory conducted by the USDA Forest Service, Forest Inventory and Analysis (FIA) program [7]. Broad forest ecosystem components (e.g., aboveground live biomass) have been delineated to generalize C stocks to meet international reporting agreements pursuant to refining understanding of global carbon cycling [2,3]. Carbon estimates for the ecosystem components of forest floor (inclusive of litter, fine woody debris, and humic soil horizons), down dead wood, belowground (BG) biomass, and soil organic matter are calculated by FIA using models based on geographic area, forest type, and, in some cases, stand age [6,8]. Estimates of aboveground (AG) standing live and dead tree C stocks are based on biomass estimates obtained from inventory tree data [6,9]. Although forest C stock estimates, such as those from FIA, are readily available at national and regional scales [6,7], there is increasing interest in disaggregating these large-scale numerical estimates into maps of continuous estimates to enable strategic forest management and monitoring activities geared toward offsetting GHG emissions [10] and advancing C dynamics research.Secondary to the need for spatially continuous forest C maps, numerous constituents (e.g., m


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